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» Evaluating algorithms that learn from data streams
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WAIM
2010
Springer
15 years 1 months ago
An Efficient Approach for Mining Segment-Wise Intervention Rules in Time-Series Streams
Huge time-series stream data are collected every day from many areas, and their trends may be impacted by outside events, hence biased from its normal behavior. This phenomenon is ...
Yue Wang, Jie Zuo, Ning Yang, Lei Duan, Hong-Jun L...
WWW
2009
ACM
16 years 4 months ago
Constructing folksonomies from user-specified relations on flickr
Automatic folksonomy construction from tags has attracted much attention recently. However, inferring hierarchical relations between concepts from tags has a drawback in that it i...
Anon Plangprasopchok, Kristina Lerman
WWW
2008
ACM
16 years 4 months ago
Mining the search trails of surfing crowds: identifying relevant websites from user activity
The paper proposes identifying relevant information sources from the history of combined searching and browsing behavior of many Web users. While it has been previously shown that...
Mikhail Bilenko, Ryen W. White
ICDM
2008
IEEE
142views Data Mining» more  ICDM 2008»
15 years 10 months ago
Clustering Events on Streams Using Complex Context Information
Monitoring applications play an increasingly important role in many domains. They detect events in monitored systems and take actions such as invoke a program or notify an adminis...
YongChul Kwon, Wing Yee Lee, Magdalena Balazinska,...
118
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SSPR
2004
Springer
15 years 9 months ago
Learning from General Label Constraints
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
Tijl De Bie, Johan A. K. Suykens, Bart De Moor